Numerical investigations on pilot ignited high pressure direct injection natural gas engines: A review

Menghan Li, Hanming Wu, Xiaori Liu, Zhangning Wei, Hongjian Tian, Qiang Zhang and Zhenguo Li

Renewable and Sustainable Energy Reviews, 2021, vol. 150, issue C

Abstract: Pilot ignited high pressure direct injection natural gas engines have a lower tendency of end-wall gas formation owing to the fuel introduction method. Thus, this type of engines are adaptable to high compression ratios and have the potential to achieve low emission levels. In this paper, numerical investigations concerning underexpanded gas jets and in-cylinder working process of pilot ignited high pressure direct injection natural gas engines are involved. The different numerical models adopted in the previous studies are systematically evaluated, giving guidance for the selection of numerical methods during the development of pilot ignited natural gas engines. The results indicate that analytical models could predict jet penetration with high accuracy while Mach disk height and diameter could be well reproduced by empirical correlations. Computational fluid dynamic models could provide more detailed information of jet flow fluid compared to analytical models and empirical correlations. Among all the computational fluid dynamic models, RANS models are considered as the most computational efficient ones while DNS is the most time consuming choice. If only the macro parameters are concerned, RANS models are the best choices. However, if near-field detailed structures are emphasized, using LES models is a better solution. When conducting three-dimensional simulations of the engine working process, RANS models are the most efficient choices for the modeling of in-cylinder flow field while reduced dual fuel mechanism coupled with phenomenological soot models could capture the in-cylinder combustion and emission formation processes with high-precision.

Keywords: Natural gas engine; High pressure direct injection; Underexpanded gas jet; Numerical study; Computational fluid dynamics model (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.rser.2021.111390

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